Cancer Breakthroughs Meet Market Realities

By Virginia Postrel -
Oct 31, 2012

When Apostolia M. Tsimberidou was a
young hematologist, a diagnosis of chronic myelogenous leukemia
meant a patient had only a few years to live.

The median survival time when she started medical school in
1985, she recalls, was just 3.5 years. Then came Novartis Inc.’s (NOVN)
Gleevec, or imatinib, which the Food and Drug Administration
approved in 2001. Unlike traditional chemotherapy drugs, which
work by poisoning the body’s fast-growing cells, Gleevec is a
so-called biologic that works by altering the behavior of
abnormal protein molecules -- in this case, inhibiting an enzyme
that makes the cancer cells proliferate.

With Gleevec, the death rate for patients with the disease
plummeted to only 1 percent or 2 percent a year. The estimated
8-year survival rate has increased from 6 percent before 1975 to
87 percent since 2001. The drug, says Tsimberidou, “changed
dramatically the survival of patients with this disease.”

That striking success made her want to find more
molecularly tailored treatments when she moved in 2007 from
hematology to designing “Phase I” human trials in a new
department at the University of Texas’s MD Anderson Cancer
Center in Houston. But chronic myelogenous leukemia is an
unusual case, because almost all patients have the same
molecular abnormality and therefore are candidates for Gleevec.

Fragmented Cancers

When analyzed at the molecular level, a cancer that has
traditionally been viewed as a single disease commonly fragments
into many different subtypes, each possibly requiring a
different treatment. There are now tests for about 200 different
such abnormalities, which may occur by themselves or in
combination.

“We should realize first that every patient is different,”
says Tsimberidou. “We cannot treat all patients with, say,
colorectal cancer the same or think, for instance, that all
metastatic liver disease is the same. In addition to the
standard diagnostic procedures, we should perform a more refined
tumor molecular analyses to better characterize every patient’s
disease, and we have to tailor the treatment to the specific
tumor and patient characteristics.”

The molecular understanding of cancer means both good news
and bad news for improving treatment.

The good news is that more cures should be possible, with
less waste from giving the wrong patients drugs that won’t work
in their particular cases. That potentially could save money and
significantly reduce suffering.

The patients in Phase I trials, which test brand new drugs
for safety and dosage rather than efficacy, are usually in a bad
place. Their cancers are advanced, and they’ve already had lots
of treatments. In short, they’re dying. They’re willing to be
guinea pigs on the off-chance that something new might buy them
some time.

Traditionally, “there was no particular expectation that
you would even see any responses in a Phase I setting,” says
George Sledge, a professor at the Indiana University School of
Medicine and the former president of the American Society of
Clinical Oncology.

But Tsimberidou believed she could do better, using
molecular information, even at the earliest stage of drug
trials. In research reported in September in Clinical Cancer
Research, she and her co-authors first performed molecular
analyses of patients’ tumors to identify genetic abnormalities
in patients with advanced cancer who had volunteered for Phase I
trials. They then assigned patients to trials based on the
tests.

Remarkable Response

The results were striking. Only about 5 percent of patients
who weren’t assigned to drugs based on molecular profiles
responded to treatment, which is typical for Phase I trials. By
contrast, 27 percent of patients in the matched therapy -- those
who got therapy targeting the specific molecular abnormalities
in their tumors -- responded.

Other measures tell the same story. The median time-to-
treatment-failure was 5.2 months for the matched-therapy group,
compared with 2.2 months for unmatched patients, and the median
survival time was 13.4 months, compared with nine months.

The two groups were not randomly assigned, so it’s of
course possible that some hidden factor accounts for the
disparate results. But given that these were very sick patients
who already had lots of treatments, and that they had many
different kinds of tumors, even with a nonrandomized group the
differences are great enough that it looks like Tsimberidou’s
team is on to something real.

“When you’re talking about a five-fold improvement in a
Phase I response rate over what you see historically, that
implies that very early in the development process now we should
be able to get some sense of whether or not a drug is active,”
said an impressed Sledge.

Tsimberidou is now developing a randomized trial to test
the concept.

Since June 2011, she and her team have also doubled the
number of patients they’ve tested, finding even more molecular
aberrations they might potentially match with new drugs. About
52 percent of patients have shown at least one abnormality, 11
percent have two, and 2.5 percent have three or more. A recent
patient even turned up with 10 molecular aberrations. And
therein lies the bad news.

The first problem is that not every abnormality has
anything to do with the cancer. Some are just, in Tsimberidou’s
phrase, “cosmetic” -- correlated with a cancer but not causal.
That poses a scientific challenge. To develop effective
treatments, researchers have to figure out which biomarkers are
relevant and should therefore be attacked with drugs.

Then there’s the economic problem.

It costs something like $1 billion to develop a new drug
and bring it through testing to market. That cost, plus profit,
needs to be spread over a lot of patients.

Orphan Diseases

For blockbuster biologics like Gleevec or Genentech Inc.’s (ROG)
Herceptin, which treats HER2-positive breast cancer, the right
patients are numerous and easily identifiable. But most
mutations -- or combinations of mutations -- are much rarer,
making the markets for drugs to address them much smaller.
Sledge points, for example, to Pfizer Inc. (PFE)’s Xalkori, or
crizotinib, which treats lung cancer in just 5 percent of
patients with a particular mutation.

As cancers and treatments are defined more and more
precisely at the molecular level, nearly every form of cancer
could become an “orphan disease” with a narrow, potentially
unprofitable market for drugs.

“Your markets become a lot smaller,” said Meredith Buxton,
the program director of I-SPY, a University of California at San
Francisco program doing human trials of potential breast-cancer
drugs. “That’s the dilemma. The more people learn that breast
cancer is not a homogeneous disease -- that it’s many different
little diseases -- the less the value for a company to put in
the $1 billion for a drug that’s going to be for a fairly
specific and small-market.”

I-SPY is trying to turn the problem around by matching
drugs to biomarkers and speeding up human trials. Testing drugs
on patients who have the wrong kind of tumors is, after all,
expensive and inefficient.

“The high cost of oncology drug development is not only an
issue of finance but also occurs because many cancers are
heterogeneous,” wrote Laura Esserman, the UCSF professor who
founded I-SPY, and Janet Woodcock, the director of the U.S. Food
and Drug Administration’s Center for Drug Evaluation and
Research, in a December 2011 journal article. They called for
“new clinical trial designs that account for the heterogeneity
and complexity of the specific disease at the outset.”

Safeway Subsidy

I-SPY does just that, using two novel approaches to speed
up Phase II trials testing the efficacy of about a half-dozen
new drugs for breast cancer. (Although the I-SPY program focuses
on breast cancer, Esserman’s specialty, and receives funding
from, among other sources, the money Safeway Inc. (SWY) supermarket
customers chip in during breast-cancer-awareness month,
researchers hope oncologists treating other types of cancer will
adopt the tools and processes it has developed.)

Patients in the program have been newly diagnosed, but they
already have large tumors. Everybody gets the standard
treatment, but some patients are randomly assigned to also get
one of the new drugs.

The first twist is that instead of treating patients with
drugs after they’ve had surgery, and then waiting five years to
see whether the cancer recurs, I-SPY uses the drugs first and
tracks the size of the tumor over the six or seven months until
surgery. If the tumor disappears by the time of the surgery,
that qualifies as a “pathologic complete response.” Enough such
results allow a new drug to move on to Phase III trials -- years
earlier than the traditional approach.

The second twist is an adaptive, or Bayesian, design.
Patients’ tumors are analyzed for biomarkers when they start the
program. If patients with certain abnormalities do particularly
well on a certain drug, new patients coming into the trial with
that same biomarker will have a higher probability of being
given that drug. Over time, drugs that do badly are dropped and
those that do well progress. The experimental design cuts the
time and number of patients needed for testing. In theory, drugs
that graduate to Phase III trials should have an 85 percent
chance of succeeding in that final, tougher and much more
expensive stage -- much better odds than the typical trial.

“If we find a faster, less expensive way to provide these
drugs,” said Buxton, “then companies will feel like it’s worth
it to continue to test them.”

Understanding the molecular differences among cancers may
be interesting science. But without economically feasible
treatments, it won’t do much for patients.

(Virginia Postrel is a Bloomberg View columnist. This is
the second part of a two-part series; read part one. She is the
author of “The Future and Its Enemies” and “The Substance of
Style,” and is writing a book on glamour. Follow her on Twitter
@vpostrel. The opinions expressed are her own.)